The injection molding process is an established method for the primary forming of plastic component parts in industry. It is frequently used in larger productions. So far, fundamental, quality-monitoring measures have been integrated into injection molding machines. Because of changes in the process and because of external influences on these, however, even using the same machine parameters and process parameters, component parts may be produced that have different qualities. Up to now, preponderantly only changes in the process signals have been recognized when, for example, a previously defined envelope or tolerance for process characteristic variables are exceeded or undershot. In this case, the corresponding component parts are rejected via a quality gate. This functionality is integrated into most of the current injection molding machines. This process valuation is relatively inaccurate, however, since the quality features are not directly valued, and it does not enable regulation of the process. An adjustment of the machine parameters requires the intervention of an operator, and as a rule, takes place only after scrap has already been produced. The adjustment of the injection molding parameters takes place according to the experience of the operator, since the quality factors of the component part, depending on the component part, act differently on individual machine parameters.
German document DE 101 204 76 A1 discusses a hybrid model and a method for determining the properties with respect to fabricating an injection molded part which is made up of one or more neural network and having rigorous models which are interconnected. The rigorous models are used for imaging submodels that are operable using mathematical formulas. The neural submodel is used for imaging processes whose connection is present only in the form of data, and which are not able to be modeled rigorously. By the combination of the methods, the prognosis of process times and processing properties during the injection molding of plastic molded parts is supposed to be clearly improved. The method described supplies prognoses based on characteristic features of the process and of the material to be processed to form thermal and rheological processing properties and for the cycle time. However, no regulation takes place, in DE 101 204 76 A1, of the process with respect to quality features of the fabricated injection molded parts.
In DE 102 417 46 A1, a method is discussed for quality valuation and process monitoring in cyclical production processes, a distinction being made between a setting phase I, a setting phase II and a working phase, and a quality valuation taking place of the products fabricated in the cyclical production process with the aid of a set of quality features, an automatic working point optimization, a generation of a first training data set, an automatic selection of characteristic variables and a self-generating process model going into the first setting phase, which is taken over into the working phase. Besides the process model, the latter includes a quality valuation module and a process monitoring module and, at inadmissible deviations, provides for random sampling in a setting phase II, which leads to generating an additional training data set, having subsequent renewed characteristic variable selection and adjustment of the self-generating process model, which is thereafter taken over into the working phase. The quality valuation and the process monitoring take place, in this instance, in separate phases or cycles, that are required in addition to the actual injection molding process, whereby the overall method sequence takes very much time and is very costly.